English

Queueing models with random resetting

Probability 2025-11-27 v3

Abstract

We introduce and study some queueing models with random resetting, including Markovian and non--Markovian models. The Markovian models include M/M/\infty, M/M/r and M/M/1+M queues with random resetting, in which a continuous-time Markov chain is formulated, with transitions including a resetting to state zero in addition to arrivals and services. We explicitly characterize the stationary distributions of the queueing processes in these models by using parting balance equations. Although the stationary distribution for M/M/\infty queue with resetting has been previously derived in the literature, we obtain an alternative and more interpretable expression by a different approach. That provides useful insights for the analysis of M/M/r and M/M/1+M queues with resetting under the first-come first-served (FCFS) discipline. The non--Markovian models include GI/GI/1, GI/GI/rr and GI/GI/\infty queues with random resetting to state zero at arrival times. For GI/GI/1 and GI/GI/rr queues under the FCFS discipline, we introduce modified Lindley and Kiefer--Wolfowitz recursions, respectively. Using an operator representation for these recursions, we characterize the stationary distributions via convergent series, as solutions to the modified Wiener--Hopf equations. For GI/GI/\infty queues with resettings, we utilize a version of the Kiefer--Wolfowitz recursion, and also characterize the corresponding stationary distribution.

Keywords

Cite

@article{arxiv.2505.00198,
  title  = {Queueing models with random resetting},
  author = {Dongzhou Huang and Guodong Pang and Izabella Stuhl and Yuri Suhov},
  journal= {arXiv preprint arXiv:2505.00198},
  year   = {2025}
}